Hybrid Workplace Management System [ HWMS ]¶

In [98]:
display(Image(filename='input/image1.JPG'))
In [99]:
display(Image(filename='input/problem_statement.JPG'))
In [100]:
display(Image(filename='input/benefits.JPG'))
In [101]:
display(Image(filename='input/architecture.png'))
In [32]:
# Distrubution of Employees over the Week
new_df.dayofweek.hist()
Out[32]:
<Axes: >
In [38]:
Distribution_of_employees.plot(figsize=(12,6))
Out[38]:
<Axes: xlabel='Working_Date'>
In [49]:
Distribution_of_vender_transactions.plot(figsize=(12,6))
Out[49]:
<Axes: xlabel='Transaction_Date'>

Forecast Employees and Vendor Transaction Data¶

- Prophet: Automatic Forecasting Procedure on time-series data based¶
- Non-linear trends are fit with yearly, weekly, and daily seasonality, plus holiday effects¶
In [81]:
# Forecast data for 30 days 
fig1 = model.plot(forecast)
In [88]:
# Interactive plot for 365 days
plot_plotly(model, forecast)
In [89]:
plot_components_plotly(model, forecast)

Seasonality, Holiday Effects, And Regressors¶

In [96]:
fig = model.plot_components(forecast)

Thank You 🎈¶